Late-life depression (LLD) applies to adults ages 65 and older and has an average estimated global prevalence of 31.8%, making it a common mental health issue (Zhao, 2023). A 2020 article that examined NHANES data found the prevalence of severe depression in American older adults significantly increased between the years 2005 and 2016 (Yu et al., 2020). This LLD prevalence was likely exacerbated due to the COVID-19 pandemic (Robinson et al., 2022).
The line graph below displays changes in the prevalence of late-life depression in the United States between the years 2011 and 2022. Late-life depression has increased from 13% in 2011 to 15.5% in 2022. Additionally, there has been a recent increase since 2020.
This project first uses supplementary data to give context regarding the prevalence of late-life depression in the United States (https://www.statista.com/statistics/1472240/depression-among-the-elderly-population-us/), and then, since the actual data cannot publicly be made available, uses replicated data from the REMBRANDT study. The REMBRANDT study provides patient characteristics, depression recurrence dates, and longitudinal physical activity data collected using wearable technology consisting of 132 patients who are ages 60 and above and enrolled between 2020 and 2024 from three different clinical sites: University of Illinois at Chicago, University of Pittsburgh, and Vanderbilt University Medical Center in Nashville, Tennessee. There are three different types of patients, those who never had depression (Healthy Controls), and remitted patients who were treated for depression at the beginning of the study. Remitted patients were followed and depressive episode dates were recorded (Relapsed or No Relapse). Patients in the replicated REMBRANDT study data had four recorded activity sessions each using data collected using FitBits and the average of each physical activity variable was calculated for each session.
To preserve data privacy, the spaghetti plot below shows replicated data from the REMBRANDT study, and specifically displays each patient’s change in sedentary time between each activity session. The patient data is separated by patient type, and red X’s indicate when a depressive episode, or relapse, occurred during the study period of 2 years. This graph shows the majority of relapses occurred when sedentary time was high.
This project further integrates wearable technology into mental health research and emphasizes the relationship between inactivity and late-life depression. The visualizations inspire further research on late-life depression and promote physical activity as a potential preventative measure.
America’s Health Rankings. (2023, July 1). Share of adults aged 65 years and above who were diagnosed with depression in the U.S. from 2011 to 2022. Statista. Retrieved February 20, 2025, from https://www.statista.com/statistics/1472240/depression-among-the-elderly-population-us/
Robinson, E., Sutin, A. R., Daly, M., & Jones, A. (2022). A systematic review and meta-analysis of longitudinal cohort studies comparing mental health before versus during the COVID-19 pandemic in 2020. Journal of affective disorders, 296, 567–576. https://doi.org/10.1016/j.jad.2021.09.098
Vanderbilt University Medical Center. (n.d.). Rembrandt study. Laboratory of Affective and Cognitive Imaging. https://www.vumc.org/laci/rembrandt-study
Yu, B., Zhang, X., Wang, C., Sun, M., Jin, L., & Liu, X. (2020). Trends in depression among adults in the United States, NHANES 2005–2016. Journal of Affective Disorders, 263, 609-620. https://doi.org/10.1016/j.jad.2019.11.036
Zhao, Y., Wu, X., Tang, M., Shi, L., Gong, S., Mei, X., Zhao, Z., He, J., Huang, L., & Cui, W. (2023). Late-life depression: Epidemiology, phenotype, pathogenesis and treatment before and during the COVID-19 pandemic. Frontiers in psychiatry, 14, 1017203. https://doi.org/10.3389/fpsyt.2023.1017203